code: def MAC_metrics(
      *, minibatch=False, epoch=False, experience=False
  ) -> List[PluginMetric]:
      """
      Helper method that can be used to obtain the desired set of
      plugin metrics.
  
      :param minibatch: If True, will return a metric able to log
          the MAC after each iteration at training time.
      :param epoch: If True, will return a metric able to log
          the MAC after each epoch at training time.
      :param experience: If True, will return a metric able to log
          the MAC after each eval experience.
  
      :return: A list of plugin metrics.
      """
  
      metrics: List[PluginMetric] = []
      if minibatch:
          metrics.append(MinibatchMAC())
  
      if epoch:
          metrics.append(EpochMAC())
  
      if experience:
          metrics.append(ExperienceMAC())
  
      return metrics
  
imports: from torch.nn import Module
  from typing import List, Optional
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
label_desc: Use image node_id 1 for calling a global function with example usage: MAC_metrics() and returns: metrics